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Related Concept Videos

Proteomics01:33

Proteomics

7.5K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Peptide Identification Using Tandem Mass Spectrometry01:33

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Related Experiment Video

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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MOPED enables discoveries through consistently processed proteomics data.

Roger Higdon, Elizabeth Stewart, Larissa Stanberry

    Journal of Proteome Research
    |December 20, 2013
    PubMed
    Summary
    This summary is machine-generated.

    The Model Organism Protein Expression Database (MOPED) is an expanding proteomics resource. It provides standardized protein expression data from various organisms to aid biological and biomedical research.

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    Area of Science:

    • Proteomics
    • Bioinformatics
    • Systems Biology

    Background:

    • The Model Organism Protein Expression Database (MOPED) serves as a crucial proteomics resource.
    • It aggregates standardized protein expression and metadata from mass spectrometry experiments across human and model organisms.

    Purpose of the Study:

    • To enhance MOPED with new protein abundance, concentration, and differential expression data.
    • To improve the query interface for easier data exploration by organism, tissue, localization, condition, experiment, or keyword.
    • To support the Human Proteome Project and facilitate multi-omics data integration.

    Main Methods:

    • Aggregation of proteomics data from human and model organisms (mouse, worm, yeast).
    • Implementation of a new query interface for comprehensive data exploration.
    • Integration of links to chromosome and disease information, supporting the Human Proteome Project.
    • Development of an omics metadata checklist for data harmonization.

    Main Results:

    • MOPED now includes updated estimates of protein abundance, concentration, and relative expression.
    • An improved query interface allows for detailed exploration of proteomics data.
    • Enhanced support for the Human Proteome Project and disease-specific proteomes.
    • A new omics metadata checklist promotes standardized data integration and analysis.

    Conclusions:

    • MOPED's latest version offers expanded proteomics data and improved accessibility for biological discovery.
    • Community-driven development is transforming MOPED into a multi-omics resource.
    • Standardized data submission and the metadata checklist will foster deeper insights into complex biological systems.